Is your phone so smart to affect your state? An exploratory study based on psychophysiological measures

Is having your cell phone the key to happiness, or does it really matter? Evidence from a randomized double-blind study

BACKGROUND

Affect can influence people's perceptions, decisions, and the way they make sense of an experience. Some studies show that having one's cell phone removed will lead to negative emotional reactions, while others have found no significant impact on how we feel. In this paper we investigate the impact of cell phone possession and removal on participant's affective state.

METHODS

We use a randomized double-blind procedure to examine whether cell phone removal enhances negativity, promotes positivity, or is emotionally inconsequential. We measure affect using a PANAS self-report scale as well as a less transparent temporal-estimation procedure.

RESULTS

Our findings suggest that cell phone possession or removal has no influence on a person's affective state.

CONCLUSIONS

Measured through both the PANAS self-report scale and temporal estimation task, affect remained consistent regardless of cell phone possession. These results suggest that cell phones may not carry the emotional weight often attributed to them. This finding challenges a common theme revolving around the negative emotional impact of cell phones and technology. Consequently, these findings may have important implications for the generally perceived notion that cell phones are having a negative effect on people's emotions.

Living Ambivalently with Chronic Illness

Mobile health smartphone applications (mHealth apps) enable patients to monitor how chronic illness interconnects with their everyday life. I explore, through focus group discussions, how such monitoring makes sense to pediatric and young patients and parents in Denmark. These groups explicate how they live both with and without chronic illness by distinguishing between when to focus on which aspects of it. I argue that this relationship with chronic illness produces parent's, children's, and young people's ambivalent attitudes toward mHealth apps that promote illness monitoring "anywhere" and at "any time."

Assessing Pharmacy Student Performance and Perceptions on Counseling Skills Through a Simulated Telehealth Encounter

Objective. To describe the implementation of a teleconferencing-based patient counseling role play assessment in a newly developed pharmacy communications course, assess student performance on the role play and compare it with other assessments, and measure student perceptions of and satisfaction with the experience.Methods. Eighteen cases were developed, each belonging to one of three interactions in community pharmacy: filling a new prescription, completing a refill, or handling a request for a nonprescription (ie, over-the-counter [OTC]) medication. A rubric was designed to evaluate each type of interaction. Student scores in various course assessments were tested and scores on the three cases were compared. Students also evaluated their experience and satisfaction of the assessment and effectiveness of the course.Results. Seventy-nine students completed the assessment, achieving a mean score of 17.4/20 (87%). Student scores in the counseling role play were similar among case types and positively correlated with other traditional assessments in the course. Despite internet connectivity issues and heightened student anxiety, 71% of students agreed that the assessment did not affect the quality of their counseling, and 74% agreed that the experience was comparable to traditional assessments. The telehealth activity led to enhanced perceived student knowledge and confidence in interviewing and counseling patients.Conclusion. Students attained high scores that were consistent with other assessments in the course. Students reported that the assessment did not affect the quality of their counseling and felt the setting and context were still authentic. The experience required dedicated preparation and organization but was successful in demonstrating overall student satisfaction and positive perceptions.

Contrastive Self-Supervised Learning for Stress Detection from ECG Data

In recent literature, ECG-based stress assessment has become popular due to its proven correlation to stress and increased accessibility of ECG data through commodity hardware. However, most ECG-based stress assessment models use supervised learning, relying on manually-annotated data. Limited research is done in the area of self-supervised learning (SSL) approaches that leverage unlabelled data and none that utilize contrastive SSL. However, with the dominance of contrastive SSL in domains such as computer vision, it is essential to see if the same excellence in performance can be obtained on an ECG-based stress assessment dataset. In this paper, we propose a contrastive SSL model for stress assessment using ECG signals based on the SimCLR framework. We test our model on two ECG-based stress assessment datasets. We show that our proposed solution results in a 9% improvement in accuracy on the WESAD dataset and 3.7% on the RML dataset when compared with SOTA ECG-based SSL models for stress assessment. The development of more accurate stress assessment models, particularly those that employ non-invasive data such as ECG for assessment, leads to developments in wearable technology and the creation of better health monitoring applications in areas such as stress management and relaxation therapy.

Effectiveness of the mHealth intervention 'MyDayPlan' to increase physical activity: an aggregated single case approach

Background

e- and mHealth interventions using self-regulation techniques like action and coping planning have the potential to tackle the worldwide problem of physical inactivity. However, they often use one-week self-regulation cycles, providing support toward an active lifestyle on a weekly basis. This may be too long to anticipate on certain contextual factors that may fluctuate from day to day and may influence physical activity. Consequently, the formulated action and coping plans often lack specificity and instrumentality, which may decrease effectiveness of the intervention. The aim of this study was to evaluate effectiveness of a self-regulation, app-based intervention called ‘MyDayPlan’. “MyDayPlan’ provides an innovative daily cycle in which users are guided towards more physical activity via self-regulation techniques such as goal setting, action planning, coping planning and self-monitoring of behaviour.

Methods

An ABAB single-case design was conducted in 35 inactive adults between 18 and 58 years (M = 40 years). The A phases (A1 and A2) were the control phases in which the ‘MyDayPlan’ intervention was not provided. The B phases (B1 and B2) were the intervention phases in which ‘MyDayPlan’ was used on a daily basis. The length of the four phases varied within and between the participants. Each phase lasted a minimum of 5 days and the total study lasted 32 days for each participant. Participants wore a Fitbit activity tracker during waking hours to assess number of daily steps as an outcome. Single cases were aggregated and data were analysed using multilevel models to test intervention effects and possible carry-over effects.

Results

Results showed an average intervention effect with a significant increase in number of daily steps from the control to intervention phases for each AB combination. From A1 to B1, an increase of 1424 steps (95% CI [775.42, 2072.32], t (1082) = 4.31,p < .001), and from A2 to B2, an increase of 1181 steps (95% CI [392.98, 1968.16], t (1082) = 2.94, p = .003) were found. Furthermore, the number of daily steps decreased significantly (1134 steps) when going from the first intervention phase (B1) to the second control phase (A2) (95% CI [− 1755.60, − 512.38], t (1082) = − 3.58, p < .001). We found no evidence for a difference in trend between the two control (95% CI [− 114.59, 197.99], t (1078) = .52, p = .60) and intervention phases (95% CI [− 128.79,284.22], t (1078) = .74, p = .46). This reveals, in contrast to what was hypothesized, no evidence for a carry-over effect after removing the ‘MyDayPlan’ app after the first intervention phase (B1).

Conclusion

This study adds evidence that the self-regulation mHealth intervention, ‘MyDayPlan’ has the capacity to positively influence physical activity levels in an inactive adult population. Furthermore, this study provides evidence for the potential of interventions adopting a daily self-regulation cycle in general.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-021-01163-2.

Antecedents of Intention to Adopt Mobile Health (mHealth) Application and Its Impact on Intention to Recommend: An Evidence from Indonesian Customers

INTRODUCTION

Mobile health (mHealth) applications gain popularity due to the increasing number of mobile phone usage and internet penetration, which might help some of Indonesia's medical issues. However, the uptake of mHealth applications is still low in Indonesia. This study is aimed at understanding the factors that drive individuals to adopt mHealth applications and their impact on the intention to recommend.

METHODS

We applied a new model that combines three different theories with some other constructs: an extended unified theory of acceptance and use of technology, diffusion of innovation, and the internet customer trust model. The study used a cross-sectional study design with partial least squares causal modeling approach.

RESULTS

There are 787 respondents in our study, with the majority of them being female, young adults. Our model could explain 53.2% of the variance of intention to adopt while explaining 48.3% of the variance of intention to recommend. Initial trust in mHealth platform (β = 0.373, p = <0.001), facilitating conditions (β = 0.131, p = <0.01), and performance expectancy (β = 0.099, p = <0.05) are the top three most important drivers of intention to adopt mHealth applications. Lastly, importance-performance map analysis (IPMA) showed that the mHealth application's initial trust is the most important construct with a high-performance score. Discussion. Mobile health developers and managers need to improve initial trust in the mHealth platform, facilitating conditions, and performance expectancy when developing the applications. With a medium Q 2 predict, these factors can be applied out of the research context with medium predictive power.

2021 ISHNE/HRS/EHRA/APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

2021 ISHNE/ HRS/ EHRA/ APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/ Heart Rhythm Society/ European Heart Rhythm Association/ Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

2021 ISHNE / HRS / EHRA / APHRS Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology / Heart Rhythm Society / European Heart Rhythm Association / Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology / Heart Rhythm Society / European Heart Rhythm Association / Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

2021 ISHNE/HRS/EHRA/APHRS Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

2021 ISHNE/HRS/EHRA/APHRS Expert Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

Bibliometric Analysis and Methodological Review of Mobile Health Services and Applications in India

PURPOSE

The purpose of this research is to analyze the literature published on mobile health (mHealth) in the Indian context. It also reviews the most important research works and presents various methodologies adopted by the researchers in this domain.

DESIGN/METHODOLOGY/APPROACH

The SciVerse SCOPUS database was used for extracting the literature on mobile health. The study used articles published between January 2008 to 28^th June 2019. The keyword used is 'mHealth' and journal articles with studies or interventions carried out in India were selected for bibliometric analysis and methodological review.

FINDINGS

For the keyword search, a total of 7,874 documents have been extracted, of which only 158 have been considered for the analysis. There is an exponential increase in the number of publications from the year 2015 to 2019. The keywords used for representing their articles have been grouped as mobile health devices, gender and age groups, system and software, health and disease condition, management, evidence-based practices (outcome), methods, and importance of the study. The journal PLOS One (87) has the highest number of citations, followed by The Lancet (63). The bibliometric analysis of the literature revealed seven clusters classified as individual's individual's mobile health applications adoption characteristics, need for mobile health and its governance, mobile phone application with the internet of things based framework for healthcare monitoring, mobile health for primary healthcare systems, authentication and security protocol for mobile healthcare, development and experimentation of mobile health application, and development and mobile health for adherence support intervention.

ORIGINALITY/VALUE

The study contributes in analyzing the bibliometrics and provides a methodological review for the journal articles published on mobile health. Previous articles considered systematic analysis of the bibliometric for mHealth, and mobile technology but less adequately discussed specifically towards Indian context which this study has embraced.

Determinants of individuals’ intention to use mobile health: insights from India

Purpose

This study aims to examine the determinants of mobile health technology and applications use intention. The factors are delineated from prior literature and theories of individual traits and adoption characteristics, technology acceptance and health belief.

Design/methodology/approach

Data from 409 respondents were collected from Indian participants through a questionnaire survey. The construct “use intention” was measured using individual traits to mobile services, subjective norm, health consciousness, awareness and perceived usefulness, and the model was tested.

Findings

The study found that mobile health technology and the applications awareness and personal innovativeness influence intention to use.

Originality/value

Previous studies have often looked at technology adoption and acceptance models separately and are less adequately discussed in the Indian context. The components that determine mobile health technology and the applications’ acceptance by literature and theories of individual traits and adoption characteristics, technology acceptance and health beliefs were also inadequately discussed. The significant contribution of this research also includes policy recommendations for improving mobile health acceptance in India.

Computational Psychometrics Using Psychophysiological Measures for the Assessment of Acute Mental Stress

The goal of this study was to provide reliable quantitative analyses of psycho-physiological measures during acute mental stress. Acute, time-limited stressors are used extensively as experimental stimuli in psychophysiological research. In particular, the Stroop Color Word Task and the Arithmetical Task have been widely used in several settings as effective mental stressors. We collected psychophysiological data on blood volume pulse, thoracic respiration, and skin conductance from 60 participants at rest and during stressful situations. Subsequently, we used statistical univariate tests and multivariate computational approaches to conduct comprehensive studies on the discriminative properties of each condition in relation to psychophysiological correlates. The results showed evidence of a greater discrimination capability of the Arithmetical Task compared to the Stroop test. The best predictors were the short time Heart Rate Variability (HRV) indices, in particular, the Respiratory Sinus Arrhythmia index, which in turn could be predicted by other HRV and respiratory indices in a hierarchical, multi-level regression analysis. Thus, computational psychometrics analyses proved to be an effective tool for studying such complex variables. They could represent the first step in developing complex platforms for the automatic detection of mental stress, which could improve the treatment.

An mHealth App for Users with Dexterity Impairments: Accessibility Study

BACKGROUND

A mobile health (mHealth) system called iMHere (interactive mobile health and rehabilitation) was developed to support individuals with chronic conditions and disability in their self-management regimens. The initial design of iMHere, however, lacked sufficient accessibility for users with a myriad of dexterity impairments. The accessibility of self-management apps is essential in ensuring usability.

OBJECTIVE

This study aims to increase the usability of the iMHere system for users with dexterity impairments by increasing the app's accessibility.

METHODS

We targeted the accessibility redesign by focusing on the physical presentation and the navigability of the iMHere apps. Six participants presenting with dexterity impairments were included in the usability study of the original and redesigned apps.

RESULTS

We observed a lower number of touches needed to complete tasks (P=.09) and time to complete individual tasks (P=.06) with the redesigned app than with the original app; a significantly lower time for users to complete all tasks (P=.006); and a significantly lower error rate (P=.01) with the redesigned app than with the original app. In fact, no errors occurred with use of the redesigned app. Participant-reported overall average usability of the redesigned app (P=.007) and usability of individual modules (P<.001) were significantly higher than that of the original app due mostly to better ease of use and learnability, interface quality, and reliability.

CONCLUSIONS

Improved usability was achieved using a redesigned app. This study offers insight into the importance of personalization in enhancing the accessibility and also identifies strategies for improving usability in app development.

Mobile Technologies for Managing Heart Failure: A Systematic Review and Meta-analysis

BACKGROUND

Randomized clinical trials (RCTs) conducted among heart failure (HF) patients have reported that mobile technologies can improve HF-related outcomes. Our aim was to conduct a meta-analysis to evaluate m-Health's impact on healthcare services utilization, mortality, and cost.

METHODS

We searched MEDLINE, Cochrane, CINAHL, and EMBASE for studies published between 1966 and May-2017. We included studies that compared the use of m-Health in HF patients to usual care. m-Health is defined as the use of mobile computing and communication technologies to record and transmit data. The outcomes were HF-related and all-cause hospital days, cost, admissions, and mortality.

RESULTS

Our search strategy resulted in 1,494 articles. We included 10 RCTs and 1 quasi-experimental study, which represented 3,109 patients in North America and Europe. Patient average age range was 53-80 years, New York Heart Association (NYHA) class III, and Left Ventricular Ejection Fraction <50%. Patients were mostly monitored daily and followed for an average of 6 months. A reduction was seen in HF-related hospital days. Nonsignificant reductions were seen in HF-related cost, admissions, and mortality and total mortality. We found no significant differences for all-cause hospital days and admissions, and an increase in total cost.

CONCLUSIONS

m-Health reduced HF-related hospital days, showed reduction trends in total mortality and HF-related admissions, mortality and cost, and increased total costs related to more clinic visits and implementation of new technologies. More studies reporting consistent quality outcomes are warranted to give conclusive information about the effectiveness and cost-effectiveness of m-Health interventions for HF.

A real-time stress classification system based on arousal analysis of the nervous system by an F-state machine

BACKGROUND AND OBJECTIVE

Detection and labelling of an increment in the human stress level is a contribution focused principally on improving the quality of life of people. This work is aimed to develop a biophysical real-time stress identification and classification system, analysing two noninvasive signals, the galvanic skin response and the heart rate variability.

METHODS

An experimental procedure was designed and configured in order to elicit a stressful situation that is similar to those found in real cases. A total of 166 subjects participated in this experimental stage. The set of registered signals of each subject was considered as one experiment. A preliminary qualitative analysis of the signals collected was made, based on previous counselling received from neurophysiologists and psychologists. This study revealed a relationship between changes in the temporal signals and the induced stress states in each subject. To identify and classify such states, a subsequent quantitative analysis was performed in order to determine specific numerical information related to the above mentioned relationship. This second analysis gives the particular details to design the finally proposed classification algorithm, based on a Finite State Machine.

RESULTS

The proposed system is able to classify the detected stress stages at three levels: low, medium, and high. Furthermore, the system identifies persistent stress situations or momentary alerts, depending on the subject's arousal. The system reaches an F₁ score of 0.984 in the case of high level, an F₁ score of 0.970 for medium level, and an F₁ score of 0.943 for low level.

CONCLUSION

The resulting system is able to detect and classify different stress stages only based on two non invasive signals. These signals can be collected in people during their monitoring and be processed in a real-time sense, as the system can be previously preconfigured. Therefore, it could easily be implemented in a wearable prototype that could be worn by end users without feeling to be monitored. Besides, due to its low computational, the computation of the signals slopes is easy to do and its deployment in real-time applications is feasible.

Bibliometric analysis of worldwide scientific literature in mobile - health: 2006-2016

BACKGROUND

The advancement of mobile technology had positively influenced healthcare services. An emerging subfield of mobile technology is mobile health (m-Health) in which mobile applications are used for health purposes. The aim of this study was to analyze and assess literature published in the field of m-Health.

METHODS

SciVerse Scopus was used to retrieve literature in m-Health. The study period was set from 2006 to 2016. ArcGIS 10.1 was used to present geographical distribution of publications while VOSviewer was used for data visualization. Growth of publications, citation analysis, and research productivity were presented using standard bibliometric indicators.

RESULTS

During the study period, a total of 5465 documents were published, giving an average of 496.8 documents per year. The h-index of retrieved documents was 81. Core keywords used in literature pertaining to m-Health included diabetes mellitus, adherence, and obesity among others. Relative growth rate and doubling time of retrieved literature were stable from 2009 to 2015 indicating exponential growth of literature in this field. A total of 4638 (84.9%) documents were multi-authored with a mean collaboration index of 4.1 authors per article. The United States of America ranked first in productivity with 1926 (35.2%) published documents. India ranked sixth with 183 (3.3%) documents while China ranked seventh with 155(2.8%) documents. VA Medical Center was the most prolific organization/institution while Journal of Medical Internet Research was the preferred journal for publications in the field of m-Health. Top cited articles in the field of m-Health included the use of mobile technology in improving adherence in HIV patients, weight loss, and improving glycemic control in diabetic patients.

CONCLUSION

The size of literature in m-Health showed a noticeable increase in the past decade. Given the large volume of citations received in this field, it is expected that applications of m-Health will be seen into various health aspects and health services. Research in m-Health needs to be encouraged, particularly in the fight against AIDS, poor medication adherence, glycemic control in Africa and other low income world regions where technology can improve health services and decrease disease burden.

Would mobile health be a solution to rehospitalization?

It has been well-established that social environmental factors can increase the risk of rehospitalization for people receiving home healthcare services. For caregivers who might be challenged to keep up with sometimes unfamiliar health monitoring tasks or to know when to seek help, mobile health technology offers the potential to enhance the skills of informal caregivers and to improve the communication between home and clinical care. This paper described our recent work to determine the usability, functionality, and style of interaction that would be needed to provide an effective and well-accepted tool. Caregivers would likely adopt new mobile health tools, as long as care is taken to eliminate potential barriers, for example, by providing adequate training, and to include design aspects that enhance one's motivation to use a tool, such as by supporting autonomy and engagement.

Smartphone-Based Psychotherapeutic Micro-Interventions to Improve Mood in a Real-World Setting

BACKGROUND

Using mobile communication technology as new personalized approach to treat mental disorders or to more generally improve quality of life is highly promising. Knowledge about intervention components that target key psychopathological processes in terms of transdiagnostic psychotherapy approaches is urgently needed. We explored the use of smartphone-based micro-interventions based on psychotherapeutic techniques, guided by short video-clips, to elicit mood changes.

METHOD

As part of a larger neurofeedback study, all subjects-after being randomly assigned to an experimental or control neurofeedback condition-underwent daily smartphone-based micro-interventions for 13 consecutive days. They were free to choose out of provided techniques, including viscerosensory attention, emotional imagery, facial expression, and contemplative repetition. Changes in mood were assessed in real world using the Multidimensional Mood State Questionnaire (scales: good-bad, GB; awake-tired, AT; and calm-nervous, CN).

RESULTS

Twenty-seven men participated on at least 11 days and were thus included in the analyses. Altogether, they underwent 335, generally well-tolerated, micro-intervention sessions, with viscerosensory attention (178 sessions, 53.13%) and contemplative repetition (68 sessions, 20.30%) being the most frequently applied techniques. Mixed models indicated that subjects showed better mood [GB: b = 0.464, 95%confidence interval (CI) [0.068, 0.860], t (613.3) = 2.298, p = 0.022] and became more awake [AT: b = 0.514, 95%CI [0.103, 0.925], t (612.4) = 2.456, p = 0.014] and calmer [CN: b = 0.685, 95%CI [0.360, 1.010], t (612.3) = 4.137, p < 0.001] from pre- to post-micro-intervention. These mood improvements from pre- to post-micro-intervention were associated with changes in mood from the 1st day until the last day with regard to GB mood (r = 0.614, 95%CI [0.297, 0.809], p < 0.001), but not AT mood (r = 0.279, 95%CI [-0.122, 0.602], p = 0.167) and CN mood (r = 0.277, 95%CI [0.124, 0.601], p = 0.170).

DISCUSSION

Our findings provide evidence for the applicability of smartphone-based micro-interventions eliciting short-term mood changes, based on techniques used in psychotherapeutic approaches, such as mindfulness-based psychotherapy, transcendental meditation, and other contemplative therapies. The results encourage exploring these techniques' capability to improve mood in randomized controlled studies and patients. Smartphone-based micro-interventions are promising to modify mood in real-world settings, complementing other psychotherapeutic interventions, in line with the precision medicine approach. The here presented data were collected within a randomized trial, registered at ClinicalTrials.gov (Identifier: NCT01921088) https://clinicaltrials.gov/ct2/show/NCT01921088.

mHealth For Aging China: Opportunities and Challenges

The aging population with chronic and age-related diseases has become a global issue and exerted heavy burdens on the healthcare system and society. Neurological diseases are the leading chronic diseases in the geriatric population, and stroke is the leading cause of death in China. However, the uneven distribution of caregivers and critical healthcare workforce shortages are major obstacles to improving disease outcome. With the advancement of wearable health devices, cloud computing, mobile technologies and Internet of Things, mobile health (mHealth) is rapidly developing and shows a promising future in the management of chronic diseases. Its advantages include its ability to improve the quality of care, reduce the costs of care, and improve treatment outcomes by transferring in-hospital treatment to patient-centered medical treatment at home. mHealth could also enhance the international cooperation of medical providers in different time zones and the sharing of high-quality medical service resources between developed and developing countries. In this review, we focus on trends in mHealth and its clinical applications for the prevention and treatment of diseases, especially aging-related neurological diseases, and on the opportunities and challenges of mHealth in China. Operating models of mHealth in disease management are proposed; these models may benefit those who work within the mHealth system in developing countries and developed countries.

Development and Efficacy Testing of a Social Network-Based Competitive Application for Weight Loss

INTRODUCTION

Although a lot of people continuously try to lose weight, the obesity rate has remained high: 36.9% of males and 38.0% of females worldwide in 2013. This suggests the need for a new intervention.

MATERIALS AND METHODS

In this study, we designed a smartphone application, With U, to aid weight loss by using an offline social network of friends and an online social network, Facebook. To determine the effects of With U, this study was designed as a one-group pretest-posttest design. Overweight, obese, and severely obese adults 20-40 years old, along with their friends, participated in this study. A total of 10 pairs attempted to lose weight for 4 weeks. We used a questionnaire to measure general characteristics, motivation, and intent to continue to use With U, and the Inbody720 (Biospace, Seoul, Republic of Korea) body composition analyzer was used to measure physical characteristics. In addition, we briefly interviewed the participants about their experience.

RESULTS

We observed statistically significant effects in terms of motivation to lose weight and the amount of weight loss. Changes in physical characteristics beyond weight loss also showed positive trends. Also, we discovered some interesting facts during the interviews. The weight loss effect was greater when the team members met more and the relationship between the challengers was more direct and intimate.

CONCLUSIONS

The application With U, designed and developed to allow friends to challenge each other to lose weight, affected both motivation to lose weight and the amount of weight loss. In the future, effects of smartphone applications for health management with social networks need to be studied further.

Texting for Health: An Evaluation of a Population Approach to Type 2 Diabetes Risk Reduction With a Personalized Message

txt4health is an innovative, 14-week, interactive, population-based mobile health program for individuals at risk of type 2 diabetes, developed under the Beacon Community Program in the Greater New Orleans, La., area. A comprehensive social marketing campaign sought to enroll hard-to-reach, at-risk populations using a combination of mass media and face-to-face engagement in faith-based and retail environments. Little is known about the effectiveness of social marketing for mobile technology application in the general population. A systematic evaluation of the campaign identified successes and barriers to implementing a population-based mobile health program. Face-to-face engagement helped increase program enrollment after the initial launch; otherwise, enrollment leveled off over time. Results show positive trends in reaching target populations and in the use of mobile phones to record personal health information and set goals for reducing the risk of type 2 diabetes. The lessons from the txt4health campaign can help inform the development and programmatic strategies to provide a person-level intervention using a population-level approach for individuals at risk for diabetes as well as aid in chronic disease management.

Chronic care management of globesity: promoting healthier lifestyles in traditional and mHealth based settings

Obesity and being overweight could be real chronic conditions above all if there are other complications such as type 2 diabetes, cardiovascular diseases, hypertension, dyslipidemia, hypercholesterolemia, cancer, and various psychosocial and psychopathological disorders. Due to the multifactorial etiology of obesity, evidence-based interventions to improve weight loss, maintain a healthy weight, and reduce related comorbidities combine different treatment approaches: dietetic, nutritional, physical, behavioral, psychological, and, in some situations, pharmacological and surgical. There are significant limitations in this multidisciplinary chronic care management of obesity, most notably those regarding costs and long-term adherence and efficacy. Programs including eHealth platforms and new technologies could overcome limitations connected to the traditional in-patient chronic care management of obesity, thus providing promising opportunities in enhancing weight reduction and reducing complications in terms of long-term efficacy and effectiveness across clinical, organizational, and economic perspectives.

Study protocol: mobile improvement of self-management ability through rural technology (mI SMART)

Background

There are 62 million Americans currently residing in rural areas who are more likely to have multiple chronic conditions and be economically disadvantaged, and in poor health, receive less recommended preventive services and attend fewer visits to health care providers. Recent advances in mobile healthcare (mHealth) offer a promising new approach to solving health disparities and improving chronic illness care. It is now possible and affordable to transmit health information, including values from glucometers, automated blood pressure monitors, and scales, through Bluetooth-enabled devices. Additionally, audio and video communications technologies can allow healthcare providers to conduct many parts of a physical exam remotely from varied settings. These technologies could remove geographical distance as a barrier to care and diminish the access to care issues faced by patients who live rurally. However, currently there is lack of studies that provide evidence of feasibility, acceptability, and effectiveness of mHealth initiatives on improved outcomes of care, a needed step to make the translation to implementation studies in healthcare systems. The purpose of this paper is to present the protocol for the first study of mI SMART (mobile Improvement of Self-Management Ability through Rural Technology), a new integrated mHealth intervention.

Methods

Our objective is to provide evidence of feasibility and acceptability for the use of mI SMART in an underserved population and establish evidence for the refinement of mI SMART. The proposed study will take place at Milan Puskar Health Right, a free primary care clinic in the state of West Virginia. The clinic provides health care at no cost to uninsured, low income; adults aged 18–64 living in West Virginia. We will enroll 30 participants into this feasibility study with plans of implementing a longitudinal randomized, comparative effectiveness design in the future. Data collection will include tracking of barriers and facilitators to using mI SMART on patient and provider feedback surveys, tracking of patient-provider communications, self-reports from patients on quality of life, adherence, and self-management ability, and capture of health record data on chronic illness measures.

Discussion

We expect that the mI SMART intervention, refined from participant and provider feedback, will be acceptable and feasible. We anticipate high patient-provider satisfaction, enhanced patient-provider communication, and improved health related quality of life, adherence to treatment, and self-management ability. In addition, we hypothesize that patients who use mI SMART will demonstrate improved physical outcomes such as blood glucose, blood pressure, and weight.

Computational Psychometrics in Communication and Implications in Decision Making

Recent investigations emphasized the role of communication features on behavioral trust and reciprocity in economic decision making but no studies have been focused on the effect of communication on affective states in such a context. Thanks to advanced methods of computational psychometrics, in this study, affective states were deeply examined using simultaneous and synchronized recordings of gazes and psychophysiological signals in 28 female students during an investment game. Results showed that participants experienced different affective states according to the type of communication (personal versus impersonal). In particular, participants involved in personal communication felt more relaxed than participants involved in impersonal communication. Moreover, personal communication influenced reciprocity and participants' perceptions about trust and reciprocity. Findings were interpreted in the light of the Arousal/Valence Model and self-disclosure process.

Managing chronic pathologies with a stepped mHealth-based approach in clinical psychology and medicine

Chronic diseases and conditions typically require long-term monitoring and treatment protocols both in traditional settings and in out-patient frameworks. The economic burden of chronic conditions is a key challenge and new and mobile technologies could offer good solutions. mHealth could be considered an evolution of eHealth and could be defined as the practice of medicine and public health supported by mobile communication devices. mHealth approach could overcome limitations linked with the traditional, restricted, and highly expensive in-patient treatment of many chronic pathologies. Possible applications include stepped mHealth approach, where patients can be monitored and treated in their everyday contexts. Unfortunately, many barriers for the spread of mHealth are still present. Due the significant impact of psychosocial factors on disease evolution, psychotherapies have to be included into the chronic disease protocols. Existing psychological theories of health behavior change have to be adapted to the new technological contexts and requirements. In conclusion, clinical psychology and medicine have to face the "chronic care management" challenge in both traditional and mHealth settings.

Community pharmacy patient perceptions of a pharmacy-initiated mobile technology app to improve adherence

OBJECTIVES

To determine patient perceptions of using a demonstration application (app) of mobile technology to improve medication adherence and to identify desired features to assist in the management of medications.

METHODS

A qualitative study using key informant interviews was conducted in a community pharmacy chain for patients aged 50 and older, on statin therapy and owning a smart device.

KEY FINDINGS

Three main themes emerged from 24 interviews at four pharmacy locations, which included benefits, barriers and desired features of the app. Benefits such as accessibility, privacy, pros of appearance and beneficiaries were more likely to lead to usage of the app. Barriers that might prevent usage of the app were related to concerns of appearance, the burden it might cause for others, cost, privacy, motivation and reliability. Specific features patients desired were categorized under appearance, customization, communication, functionality, input and the app platform.

CONCLUSIONS

Patients provided opinions about using a mobile app to improve medication adherence and assist with managing medications. Patients envisioned the app within their lifestyle and expressed important considerations, identifying benefits to using this technology and voicing relevant concerns. App developers can use patient perceptions to guide development of a mobile app addressing patient medication-related needs.

Obesity and outpatient rehabilitation using mobile technologies: the potential mHealth approach

Obesity is currently an important public health problem of epidemic proportions (globesity). Inpatient rehabilitation interventions that aim at improving weight-loss, reducing obesity-related complications and changing dysfunctional behaviors, should ideally be carried out in a multidisciplinary context with a clinical team composed of psychologists, dieticians, psychiatrists, endocrinologists, nutritionists, physiotherapists, etc. Long-term outpatient multidisciplinary treatments are likely to constitute an essential aspect of rehabilitation. Internet-based technologies can improve long-term obesity rehabilitation within a collaborative approach by enhancing the steps specified by psychological and medical treatment protocols. These outcomes may be augmented further by the mHealth approach, through creating new treatment delivery methods to increase compliance and engagement. mHealth (m-health, mobile health) can be defined as the practice of medicine and public health, supported by mobile communication devices for health services and information. mHealth applications which can be implemented in weight loss protocols and obesity rehabilitation are discussed, taking into account future research directions in this promising area.

The pursuit of happiness measurement: a psychometric model based on psychophysiological correlates

Everyone is interested in the pursuit of happiness, but the real problem for the researchers is how to measure it. Our aim was to deeply investigate happiness measurement through biomedical signals, using psychophysiological methods to objectify the happiness experiences measurements. The classic valence-arousal model of affective states to study happiness has been extensively used in psychophysiology. However, really few studies considered a real combination of these two dimensions and no study further investigated multidimensional models. More, most studies focused mainly on self-report to measure happiness and a deeper psychophysiological investigation on the dimensions of such an experience is still missing. A multidimensional model of happiness is presented and both the dimensions and the measures extracted within each dimension are comprehensively explained. This multidimensional model aims at being a milestone for future systematic study on psychophysiology of happiness and affective states.

Improving diabetes management with mobile health technology

Diabetes affects 25.8 million persons in the United States, and these persons make more than 35 million ambulatory care visits annually. Yet, less than half of persons with diabetes meet the recommended levels of A1C, blood pressure and lipid control. One innovative approach is to use mobile health technologies to help patients better manage their diabetes and related conditions, and 85% to 90% of patients have access to mobile health technology. A brief review of the guidelines for diabetes care and mobile health technology that can support the guidelines are reported related to (1) glycemic control and self-monitoring of blood glucose, (2) pharmacological approaches and medication management, (3) medical nutrition therapy, (4) physical activity and resistance training, (5) weight loss, (6) diabetes self-management education and (7) blood pressure control and hypertension. The patient and provider are encouraged to explore possibilities for mobile health technologies that can support behavior change.

eHealth: extending, enhancing, and evolving health care

eHealth holds the promise of revolutionizing health care by improving its efficiency; extending and enhancing its reach; energizing and engaging its practitioners and their patients; and in the process, democratizing, decentralizing, and even partially demystifying the practice of medicine. In emerging and developing countries, the use of eHealth and smart health-care planning has the potential to expand access to necessary treatments and prevention services that can serve as underpinnings of rapid economic development. In developed countries, the application of eHealth promises to restructure the business model of health-care delivery, while at the same time improving and personalizing the quality of care received. This article reviews the past, present, and future of eHealth in an effort to illuminate the potential of its impact.